• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.7
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• pp.468-473
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• 2010

This paper deals with approximate integral solutions to the one-dimensional model describing the charging process of stratified thermal storage tanks. Temperature is assumed to be the form of Fermi-Dirac distribution function, which can be separated to two sets of cubic polynomials for each hot and cold side of thermal boundary layers. Proposed approximate integral solutions are compared to the previous works of the approximate analytic solutions and show reasonable agreement. The approach, however, has benefits in mathematical difficulties, complicated solution form and unstable convergence of series solution founded in the previous analytic solutions. Solutions for a semi-infinite region, which have simple closed form solutions, give close agreement to those for a finite region. Thermocline thickness is obtained in closed form and shows proportional behavior to the square root of time and inverse proportional behavior to the square root of flow rate.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.263-278
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• 2004

This paper reviews dynamic programming (DP), surveys approximate solution methods for it, and considers their applicability to process control problems. Reinforcement Learning (RL) and Neuro-Dynamic Programming (NDP), which can be viewed as approximate DP techniques, are already established techniques for solving difficult multi-stage decision problems in the fields of operations research, computer science, and robotics. Owing to the significant disparity of problem formulations and objective, however, the algorithms and techniques available from these fields are not directly applicable to process control problems, and reformulations based on accurate understanding of these techniques are needed. We categorize the currently available approximate solution techniques fur dynamic programming and identify those most suitable for process control problems. Several open issues are also identified and discussed.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.80-86
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• 2011

Structural optimization algorithm of steel box girder bridges using improved higher-order approximate reanalysis technique is proposed in this paper. The proposed approximation method is a generalization of the convex approximation method. The order of the approximate reanalysis for each function is analytically adjusted in the optimization process. This self-adjusted capability makes the approximate structural analysis values conservative enough to maintain the optimum design point of the approximate problem. The efficiency of proposed optimazation algorithm, compared with conventional algorithm, is successfully demonstrated in the steel box girder bridges. The efficiency and robustness of proposed algorithm is also demonstrated in practical steel box girder bridges.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.3
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• pp.160-179
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• 2023

In this paper, we investigate the existence and diameter of the approximate fixed point results on E-metric spaces (not necessarily complete) by using various cyclic contraction mappings, including the B-cyclic contraction, the Bianchini cyclic contraction, the Hardy-Rogers cyclic contraction, and so on. Additionally, we prove the approximate fixed point results for rational type cyclic contraction mappings, which were discussed mainly in [35] and [37], in the setting of E-metric space. Also, a few examples are provided to demonstrate our findings. Subsequently, we discuss some applications of approximate fixed point results in the field of applied mathematics rigorously.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.497-505
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• 2016

The two-dimensional (2D) Discrete Cosine Transform (DCT) is used widely in image and video processing systems. The perception of human visualization permits us to design approximate rather than exact DCT. In this paper, we propose a digital implementation of 16-point approximate 2D DCT architecture based on one-dimensional (1D) DCT and Modified Gate Diffusion Input (MGDI) technique. The 8-point 1D Approximate DCT architecture requires only 12 additions for realization in digital VLSI. Additions can be performed using the proposed 8 transistor (8T) MGDI Full Adder which reduces 2 transistors than the existing 10 transistor (10T) MGDI Full Adder. The Approximate MGDI 2D DCT using 8T MGDI Full adders is simulated in Tanner SPICE for $0.18{\mu}m$ CMOS process technology at 100MHZ.The simulation result shows that 13.9% of area and 15.08 % of power is reduced in the 8-point approximate 2D DCT, 10.63 % of area and 15.48% of power is reduced in case of 16-point approximate 2D DCT using 8 Transistor MGDI Full Adder than 10 Transistor MGDI Full Adder. The proposed architecture enhances results in terms of hardware complexity, regularity and modularity with a little compromise in accuracy.

• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.1-11
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• 2004

Two approximate methods for a cosmic radiation shielding calculation in low earth orbits were developed and assessed. Those are a sectoring method and a chord-length distribution method. In order to simulate a change in cosmic radiation environments along the satellite mission trajectory, IGRF model and AP(E)-8 model were used. When the approximate methods were applied, the geometrical model of satellite structure was approximated as one-dimensional slabs, and a pre-calculated dose-depth conversion function was introduced to simplify the dose calculation process. Verification was performed with mission data of KITSAT-1 and the calculated results were also compared with detailed 3-dimensional calculation results using Monte Carlo calculation. Dose results from the approximate methods were conservatively higher than Monte Carlo results, but were lower than experimental data in total dose rate. Differences between calculation and experimental data seem to come from the AP-8 model, for which it is reported that fluxes of proton are underestimated. We confirmed that the developed approximate method can be applied to commercial satellite shielding calculations. It is also found that commercial products of semi-conductors can be damaged due to total ionizing dose under LEO radiation environment. An intensive shielding analysis should be taken into account when commercial devices are used.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.204-208
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• 2000

An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity, geometrical size, and die velocity of model materials are different from those of real materials. Actually, the forming load of yoke, which is an automobile part made of aluminum alloys(Al-6061), is predicted by using this approximate similarity theory. Firstly, upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061), and a suitable model material is selected for model material test of Al-6061. And then hot forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material, which has been selected from above upset forging tests. The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

• Journal of Internet Computing and Services
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• v.14 no.1
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• pp.63-69
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• 2013

Approximate Frequent pattern mining is to find approximate patterns, not exact frequent patterns with tolerable variations for more efficiency. As the size of database increases, much faster mining techniques are needed to deal with huge databases. Moreover, it is more difficult to discover exact results of mining patterns due to inherent noise or data diversity. In these cases, by mining approximate frequent patterns, more efficient mining can be performed in terms of runtime, memory usage and scalability. In this paper, we study the characteristics of an approximate mining algorithm based on probabilistic technique and run performance evaluation of the efficient approximate frequent pattern mining algorithm. Finally, we analyze the test results for more improvement.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.431-437
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• 2003

In this paper, an approximate optimization program based on GUI(graphic user interface) environment is developed. This program is coded by using Fortran and Visual basic. Fortran is used to Progress approximate optimization process. Visual basic is used to make user environment for user to use conveniently. Inside of this program, it uses two independent programs. One is commercial program, ANSYS, and the other is optimization program, PLBA(Pshenichny-Lim-Belegundu Arora). The former is used to obtain approximate equation of stress and displacement of a structure. The latter is used to solve approximate optimization. This algorithm uses second-order information of a function and active set strategy. This program is connecting ANSYS and PLBA. And it progress the process repeatedly until it obtain optimum value. As a method of approximate optimization, sequential design domain(SDD) is introduced. SDD starts with a certain range which is offseted from midpoint of an initial design domain and then SDD of the next step is determined by optimal point of a prior step.